Industry Challenges in Retail
Low margins/profits
Retail industry is characterized by low margins due to increasing competition. This has to be offset by increasing the volumes of transactions. ScoreFast product recommendations to customers via multiple channels – Web site, email, kiosks, etc. – can increase the volumes of sales.
Competition from eCommerce vendors such as Amazon
Brick and mortar retail companies find it difficult to survive because of competition from eCommerce behemoths such as Amazon and Alibaba, which have lower costs and huge advantages of scale. ScoreFast can help expand small to large retail companies to online stores with appropriate analytics solutions.
Increasing operational costs
Operational costs of retail companies are relatively large. ScoreFast can help reduce the costs by more accurately predicting sales volumes and inventory required to meet the sales volumes.
ScoreData Solutions for Retail
Product Recommendations
- Segment the customers of a retail company based on income level, age, gender, product affinities, etc.,
- Make product recommendations based on purchases made by similar customers in that segment.
- Leverage historical data to do personalized marketing campaigns via website, email, etc.
Dynamic Pricing
- Traditional dynamic pricing is largely done using supply and demand factors.
- ScoreData also collect competitor pricing on a hourly or daily basis and incorporate that into the pricing model to maximize sales.
Sales and Inventory Forecasting
- ScoreData can provide solutions to accurately predict future sales volumes and inventory requirements to meet the volumes. This eliminates the costs of excess or inadequate inventory.
ScoreData Solutions for Retail
Product Recommendations
- Segment the customers of a retail company based on income level, age, gender, product affinities, etc.,
- Make product recommendations based on purchases made by similar customers in that segment.
- Leverage historical data to do personalized marketing campaigns via website, email, etc.
Dynamic Pricing
- Traditional dynamic pricing is largely done using supply and demand factors.
- ScoreData also collect competitor pricing on a hourly or daily basis and incorporate that into the pricing model to maximize sales.
Sales and Inventory Forecasting
- ScoreData can provide solutions to accurately predict future sales volumes and inventory requirements to meet the volumes. This eliminates the costs of excess or inadequate inventory.
Industry Challenges in Media
Availability of meaningful insights
Nodal rating agencies provide the data and software and leave to the media companies to draw insights. Media companies have to hire trained data analysts to extract the insights from the data. Shortage of trained data analysts with domain knowledge hampers extraction of meaningful insights.
Increasing Advertising revenues
Too many TV channels in general entertainment industry and it is crucial to increase the viewer “share” in order to attract more advertising. The companies current understanding of their evolving viewer profile as their tastes and needs change
Shifting consumer behavior
Media companies ability to keep up with what the viewer choice in shows
ScoreData Solutions for Media
Predicting Ratings
- Predict ratings of the TV programs for future episodes to enable the programming team to take corrective actions.
- ScoreData can explain the increase and decrease in the ratings by providing meaningful insights.
Predicting the success or failure
- ScoreData can analyze social media comments and combine it with initial ratings to predict whether a new shows launched are going to be a success or not.
Analyzing Social Media comments
- ScoreData can analyze the social media comments for a particular show and segment them.
- Generate the sentiment score and give detailed insights in addition to the comments.
ScoreData Solutions for Media
Predicting Ratings
- Predict ratings of the TV programs for future episodes to enable the programming team to take corrective actions.
- ScoreData can explain the increase and decrease in the ratings by providing meaningful insights.
Predicting the success or failure
- ScoreData can analyze social media comments and combine it with initial ratings to predict whether a new shows launched are going to be a success or not.
Analyzing Social Media comments
- ScoreData can analyze the social media comments for a particular show and segment them.
- Generate the sentiment score and give detailed insights in addition to the comments.
ScoreFast™ Approach
Data ingestion and audit
ScoreFast™ enables efficient ingestion of a wide variety of datasets including media, retail, customer data including customer behaviors and preferences, agents data, devices data, and distribution agencies data.
Algorithm selection and deployment
Based on the modeling objective (retail consumer preferences, services metrics improvement, agent empowerment, etc), ScoreFast™ sorts through a variety of algorithms and selects the best one through an iterative comparison process.
Model management and updates
Retail and Media analytics models need to be monitored for performance and updated routinely. ScoreFast™ tracks the model performance over time, and can automatically retrain a model when a degradation in performance is detected. For example, consumer retail preferences need to be updated over time, to reflect the evolving needs of the customers.
ScoreFast™ Approach
Data ingestion and audit
ScoreFast™ enables efficient ingestion of a wide variety of datasets including media, retail, customer data including customer behaviors and preferences, agents data, devices data, and distribution agencies data.
Algorithm selection and deployment
Based on the modeling objective (retail consumer preferences, services metrics improvement, agent empowerment, etc), ScoreFast™ sorts through a variety of algorithms and selects the best one through an iterative comparison process.
Model management and updates
Retail and Media analytics models need to be monitored for performance and updated routinely. ScoreFast™ tracks the model performance over time, and can automatically retrain a model when a degradation in performance is detected. For example, consumer retail preferences need to be updated over time, to reflect the evolving needs of the customers.
Retail Success Stories
Inventory Management And Sales Forecast
In last couple of year our clients launched a number of products targeting different Consumer segments and geographies. Riding on the popularity of a couple of path breaking products, they have seen an unprecedented sales growth in last couple of years across the product.
The challenge that our client was facing was optimal SKU rationalization to reduce the operational cost and reduce the TAT for the product delivery hence enhancing Consumer experience. ScoreData helped the client in their inventory management and helping them to discover seasonality and trend associated with their products at SKU level.
Resources for Retail Vertical
Retail Industry Analysis
Now a day’s huge amount of data is being captured at a rate never before seen in history of retail industry. The retailer’s goal is to translate that data into the meaningful insight so that they can make their decisions.
- How are we doing?
- Why and what we are doing?
- Why should we do in future?
Resources for Retail Vertical
Retail Industry Analysis
Now a day’s huge amount of data is being captured at a rate never before seen in history of retail industry. The retailer’s goal is to translate that data into the meaningful insight so that they can make their decisions.
- How are we doing?
- Why and what we are doing?
- Why should we do in future?
Media Success Stories
ScoreFast™ Ratings Predictions Engine For Television
Star Network is a major Asian media conglomerate netting upwards of 700 million viewers a month. They had weekly viewership ratings but sought insight into future ratings. This insight would help them proactively plan corrective action if a decline in ratings is predicted.